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Pyyan / Compare / PaddleOCR vs Qwen3-VL vs DeepSeek-OCR

PaddleOCR vs Qwen3-VL vs DeepSeek-OCR

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OCR & Document AI · verified 13 Aug 2026

×PaddleOCRBaiducurrent
×Qwen3-VLAlibabacurrent
×DeepSeek-OCRDeepSeekcurrent
2 slots left
SpecificationPaddleOCRQwen3-VLDeepSeek-OCR
SummaryThe classical workhorse, still widely deployed.A general vision model that happens to lead OCR benchmarks.Compresses pages into far fewer vision tokens.
OmniDocBench~82~93~92
Open weightsYesYesYes
HandlesText, tables, receiptsDocuments, charts, videoDense text, tables
LicenceApache 2.0Apache 2.0MIT
KindClassical engineVision language modelVision language model
CategoryOCR & Document AIOCR & Document AIOCR & Document AI
OfficialBaidu ↗Alibaba ↗DeepSeek ↗

Highlighted rows are where these differ.

PaddleOCR

  • Runs on CPU and mobile
  • Predates the VLM approach and still ships in production

Best for on-device and offline recognition.

Full spec sheet →

Qwen3-VL

  • Not an OCR model, and beats most of them
  • Sizes from 2B to 235B

Best for one model for vision and documents.

Full spec sheet →

DeepSeek-OCR

  • Treats the page image as compressed context
  • Notable for cost per page rather than raw accuracy

Best for long documents on a budget.

Full spec sheet →